{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Music Recommendation的数据集——数据探索\n",
    "\n",
    "数据集包含5个主要文件：\n",
    "1.train.csv: 训练数据(用户点击歌曲表)\n",
    "    msno: 用户id，加密String\n",
    "    song_id: song id，歌曲id\n",
    "    source_system_tab: 触发事件的类型/tab，用于表示app的功能类型\n",
    "    source_screen_name: 用户看到的布局的名字（name of the layout）\n",
    "    source_type: 用户在app上播放音乐的入口的类型\n",
    "    target: 标签。1表示用户在第一次听音乐后会在一个月内继续订阅，0表示没有订阅。\n",
    "2.test.csv: 测试数据(用户点击歌曲表)\n",
    "    id:主关键字\n",
    "    msno: 用户id，加密String\n",
    "    song_id: song id，歌曲id\n",
    "    source_system_tab: 触发事件的类型/tab，用于表示app的功能类型\n",
    "    source_screen_name: 用户看到的布局的名字（name of the layout）\n",
    "    source_type: 用户在app上播放音乐的入口的类型\n",
    "    \n",
    "用户歌曲的原数据\n",
    "3.用户表：members.csv 7个字段：\n",
    "    1）msno：用户ID \n",
    "    2）city：城市 \n",
    "    3）bd：年龄 注意：年龄数据有离群点\n",
    "    4）gender：性别\n",
    "    5）registered_via: 注册方式\n",
    "    6）registration_init_time: 注册时间，格式为%Y%m%d\n",
    "    7）expiration_date: 到期时间，格式为 %Y%m%d\n",
    "4.歌曲表：songs.csv 7个字段\n",
    "     1)song_id：歌曲id\n",
    "     2)song_length: 单位为ms\n",
    "     3)genre_ids: genre 类别. 可多选，用 “|“隔开\n",
    "     4)artist_name：歌手\n",
    "     5)composer：作曲\n",
    "     6)lyricist：作词\n",
    "     7)language：语言\n",
    "5.歌曲额外的信息表 song_extra_infos.csv 2个字段\n",
    "   1)song_id：歌曲id\n",
    "   2)song name ：歌曲名字\n",
    "   \n",
    "   项目目标：训练数据由2017年2月服务到期的用户构成，target标签代表用户在2017年3月是否续订了业务。测试集中的数据由2017年3月内将到期的用户构成，需要预测用户是否在到期后的一个月内即2017年4月预定、流失的概率。（打算选用二类分类模型解决）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "import工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dpath = './data/'\n",
    "#读入训练数据表\n",
    "#train_song=pd.read_csv(dpath +'train.csv',nrows=10000)\n",
    "train_song=pd.read_csv(dpath +'train.csv')\n",
    "song=pd.read_csv(dpath +'songs.csv')\n",
    "members=pd.read_csv(dpath +'members.csv')\n",
    "extra=pd.read_csv(dpath +'song_extra_info.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train song dataset dimensions: (7377418, 6)\n"
     ]
    }
   ],
   "source": [
    "#查看数据集和维度\n",
    "print(\"train song dataset dimensions:\", train_song.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7375849, 20)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#表合成一个总的data\n",
    "data = pd.merge(train_song,members,on=(\"msno\"))\n",
    "data = pd.merge(data,song,on=(\"song_id\"))\n",
    "data = pd.merge(data,extra,on=(\"song_id\"))\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>msno</th>\n",
       "      <th>song_id</th>\n",
       "      <th>source_system_tab</th>\n",
       "      <th>source_screen_name</th>\n",
       "      <th>source_type</th>\n",
       "      <th>target</th>\n",
       "      <th>city</th>\n",
       "      <th>bd</th>\n",
       "      <th>gender</th>\n",
       "      <th>registered_via</th>\n",
       "      <th>registration_init_time</th>\n",
       "      <th>expiration_date</th>\n",
       "      <th>song_length</th>\n",
       "      <th>genre_ids</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>composer</th>\n",
       "      <th>lyricist</th>\n",
       "      <th>language</th>\n",
       "      <th>name</th>\n",
       "      <th>isrc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FGtllVqz18RPiwJj/edr2gV78zirAiY/9SmYvia+kCg=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>explore</td>\n",
       "      <td>Explore</td>\n",
       "      <td>online-playlist</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>20120102</td>\n",
       "      <td>20171005</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>pouJqjNRmZOnRNzzMWWkamTKkIGHyvhl/jo4HgbncnM=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>discover</td>\n",
       "      <td>Online playlist more</td>\n",
       "      <td>online-playlist</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>18</td>\n",
       "      <td>male</td>\n",
       "      <td>4</td>\n",
       "      <td>20151220</td>\n",
       "      <td>20170930</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>xbodnNBaLMyqqI7uFJlvHOKMJaizuWo/BB/YHZICcKo=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>my library</td>\n",
       "      <td>Local playlist more</td>\n",
       "      <td>local-library</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>20120804</td>\n",
       "      <td>20171004</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>s0ndDsjI79amU0RBiullFN8HRz9HjE++34jGNa7zJ/s=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>my library</td>\n",
       "      <td>Local playlist more</td>\n",
       "      <td>local-library</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>21</td>\n",
       "      <td>female</td>\n",
       "      <td>9</td>\n",
       "      <td>20110808</td>\n",
       "      <td>20170917</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Vw4Umh6/qlsJDC/XMslyAxVvRgFJGHr53yb/nrmY1DU=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>my library</td>\n",
       "      <td>Local playlist more</td>\n",
       "      <td>local-library</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>33</td>\n",
       "      <td>female</td>\n",
       "      <td>9</td>\n",
       "      <td>20070323</td>\n",
       "      <td>20170915</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>YqtKhiDOFJ/gdd2V4AFdnVwGMMaA0yUEbb8w7xuoP7I=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>discover</td>\n",
       "      <td>Discover Chart</td>\n",
       "      <td>online-playlist</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>23</td>\n",
       "      <td>female</td>\n",
       "      <td>9</td>\n",
       "      <td>20141223</td>\n",
       "      <td>20171012</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>jGiECz8y+oKS0tDcZArJXK2ZQisBpk/OC3wh4kvs8gc=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>discover</td>\n",
       "      <td>Online playlist more</td>\n",
       "      <td>song-based-playlist</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>female</td>\n",
       "      <td>9</td>\n",
       "      <td>20140424</td>\n",
       "      <td>20180207</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ruQx4VOdTq74CDI1viGqQAIASWrU4soi74t1E3N6KO4=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>my library</td>\n",
       "      <td>Local playlist more</td>\n",
       "      <td>local-playlist</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>20140227</td>\n",
       "      <td>20180407</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>7xiBI5xU3P2/IiR9teB7jySfzWo96JGikGajteLd3Cs=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>my library</td>\n",
       "      <td>Radio</td>\n",
       "      <td>radio</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>41</td>\n",
       "      <td>male</td>\n",
       "      <td>7</td>\n",
       "      <td>20130909</td>\n",
       "      <td>20170923</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>z2IYoGWjJJPv4ySp+1lCIfU1APu2YRHsjY2sy2ehq0k=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>my library</td>\n",
       "      <td>Local playlist more</td>\n",
       "      <td>local-library</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>41</td>\n",
       "      <td>male</td>\n",
       "      <td>9</td>\n",
       "      <td>20110525</td>\n",
       "      <td>20170912</td>\n",
       "      <td>206471</td>\n",
       "      <td>359</td>\n",
       "      <td>Bastille</td>\n",
       "      <td>Dan Smith| Mark Crew</td>\n",
       "      <td>NaN</td>\n",
       "      <td>52.0</td>\n",
       "      <td>Good Grief</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           msno  \\\n",
       "0  FGtllVqz18RPiwJj/edr2gV78zirAiY/9SmYvia+kCg=   \n",
       "1  pouJqjNRmZOnRNzzMWWkamTKkIGHyvhl/jo4HgbncnM=   \n",
       "2  xbodnNBaLMyqqI7uFJlvHOKMJaizuWo/BB/YHZICcKo=   \n",
       "3  s0ndDsjI79amU0RBiullFN8HRz9HjE++34jGNa7zJ/s=   \n",
       "4  Vw4Umh6/qlsJDC/XMslyAxVvRgFJGHr53yb/nrmY1DU=   \n",
       "5  YqtKhiDOFJ/gdd2V4AFdnVwGMMaA0yUEbb8w7xuoP7I=   \n",
       "6  jGiECz8y+oKS0tDcZArJXK2ZQisBpk/OC3wh4kvs8gc=   \n",
       "7  ruQx4VOdTq74CDI1viGqQAIASWrU4soi74t1E3N6KO4=   \n",
       "8  7xiBI5xU3P2/IiR9teB7jySfzWo96JGikGajteLd3Cs=   \n",
       "9  z2IYoGWjJJPv4ySp+1lCIfU1APu2YRHsjY2sy2ehq0k=   \n",
       "\n",
       "                                        song_id source_system_tab  \\\n",
       "0  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=           explore   \n",
       "1  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=          discover   \n",
       "2  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=        my library   \n",
       "3  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=        my library   \n",
       "4  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=        my library   \n",
       "5  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=          discover   \n",
       "6  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=          discover   \n",
       "7  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=        my library   \n",
       "8  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=        my library   \n",
       "9  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=        my library   \n",
       "\n",
       "     source_screen_name          source_type  target  city  bd  gender  \\\n",
       "0               Explore      online-playlist       1     1   0     NaN   \n",
       "1  Online playlist more      online-playlist       0    15  18    male   \n",
       "2   Local playlist more        local-library       1     1   0     NaN   \n",
       "3   Local playlist more        local-library       1     5  21  female   \n",
       "4   Local playlist more        local-library       0     6  33  female   \n",
       "5        Discover Chart      online-playlist       0     5  23  female   \n",
       "6  Online playlist more  song-based-playlist       1     5  27  female   \n",
       "7   Local playlist more       local-playlist       1    22   0     NaN   \n",
       "8                 Radio                radio       0     5  41    male   \n",
       "9   Local playlist more        local-library       0     6  41    male   \n",
       "\n",
       "   registered_via  registration_init_time  expiration_date  song_length  \\\n",
       "0               7                20120102         20171005       206471   \n",
       "1               4                20151220         20170930       206471   \n",
       "2               7                20120804         20171004       206471   \n",
       "3               9                20110808         20170917       206471   \n",
       "4               9                20070323         20170915       206471   \n",
       "5               9                20141223         20171012       206471   \n",
       "6               9                20140424         20180207       206471   \n",
       "7               3                20140227         20180407       206471   \n",
       "8               7                20130909         20170923       206471   \n",
       "9               9                20110525         20170912       206471   \n",
       "\n",
       "  genre_ids artist_name              composer lyricist  language        name  \\\n",
       "0       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "1       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "2       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "3       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "4       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "5       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "6       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "7       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "8       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "9       359    Bastille  Dan Smith| Mark Crew      NaN      52.0  Good Grief   \n",
       "\n",
       "           isrc  \n",
       "0  GBUM71602854  \n",
       "1  GBUM71602854  \n",
       "2  GBUM71602854  \n",
       "3  GBUM71602854  \n",
       "4  GBUM71602854  \n",
       "5  GBUM71602854  \n",
       "6  GBUM71602854  \n",
       "7  GBUM71602854  \n",
       "8  GBUM71602854  \n",
       "9  GBUM71602854  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 7375849 entries, 0 to 7375848\n",
      "Data columns (total 20 columns):\n",
      "msno                      object\n",
      "song_id                   object\n",
      "source_system_tab         object\n",
      "source_screen_name        object\n",
      "source_type               object\n",
      "target                    int64\n",
      "city                      int64\n",
      "bd                        int64\n",
      "gender                    object\n",
      "registered_via            int64\n",
      "registration_init_time    int64\n",
      "expiration_date           int64\n",
      "song_length               int64\n",
      "genre_ids                 object\n",
      "artist_name               object\n",
      "composer                  object\n",
      "lyricist                  object\n",
      "language                  float64\n",
      "name                      object\n",
      "isrc                      object\n",
      "dtypes: float64(1), int64(7), object(12)\n",
      "memory usage: 1.2+ GB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#输入特征\n",
    "msno                      object  用户id不能用于预测\n",
    "song_id                   object  歌曲id不能用于预测\n",
    "source_system_tab         object  触发事件的类型/tab，用于表示app的功能类型\n",
    "source_screen_name        object  用户看到的布局的名字（name of the layout）\n",
    "source_type               object  用户在app上播放音乐的入口的类型\n",
    "city                      int64   城市\n",
    "bd                        int64   年龄 注意：年龄数据有离群点\n",
    "gender                    object  性别\n",
    "registered_via            int64   注册方式\n",
    "registration_init_time    int64   注册时间，格式为%Y%m%d\n",
    "expiration_date           int64   到期时间，格式为 %Y%m%d\n",
    "song_length               int64   歌曲长度单位为ms\n",
    "genre_ids                 object  genre 类别. 可多选，用 “|“隔开\n",
    "artist_name               object   歌手\n",
    "composer                  object   作曲\n",
    "lyricist                  object   作词\n",
    "language                  float64  语言\n",
    "name                      object   歌曲名字\n",
    "isrc                      object   isrc来源\n",
    "#输出\n",
    "target                    int64"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target</th>\n",
       "      <th>city</th>\n",
       "      <th>bd</th>\n",
       "      <th>registered_via</th>\n",
       "      <th>registration_init_time</th>\n",
       "      <th>expiration_date</th>\n",
       "      <th>song_length</th>\n",
       "      <th>language</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7.375849e+06</td>\n",
       "      <td>7.375849e+06</td>\n",
       "      <td>7.375849e+06</td>\n",
       "      <td>7.375849e+06</td>\n",
       "      <td>7.375849e+06</td>\n",
       "      <td>7.375849e+06</td>\n",
       "      <td>7.375849e+06</td>\n",
       "      <td>7.375813e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.035420e-01</td>\n",
       "      <td>7.511470e+00</td>\n",
       "      <td>1.753920e+01</td>\n",
       "      <td>6.794075e+00</td>\n",
       "      <td>2.012810e+07</td>\n",
       "      <td>2.017157e+07</td>\n",
       "      <td>2.451213e+05</td>\n",
       "      <td>1.860810e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.999875e-01</td>\n",
       "      <td>6.641632e+00</td>\n",
       "      <td>2.155224e+01</td>\n",
       "      <td>2.275785e+00</td>\n",
       "      <td>3.017261e+04</td>\n",
       "      <td>3.869916e+03</td>\n",
       "      <td>6.734491e+04</td>\n",
       "      <td>2.117688e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>-4.300000e+01</td>\n",
       "      <td>3.000000e+00</td>\n",
       "      <td>2.004033e+07</td>\n",
       "      <td>1.970010e+07</td>\n",
       "      <td>1.393000e+03</td>\n",
       "      <td>-1.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>4.000000e+00</td>\n",
       "      <td>2.011070e+07</td>\n",
       "      <td>2.017091e+07</td>\n",
       "      <td>2.147260e+05</td>\n",
       "      <td>3.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>5.000000e+00</td>\n",
       "      <td>2.100000e+01</td>\n",
       "      <td>7.000000e+00</td>\n",
       "      <td>2.013102e+07</td>\n",
       "      <td>2.017093e+07</td>\n",
       "      <td>2.418120e+05</td>\n",
       "      <td>3.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>1.300000e+01</td>\n",
       "      <td>2.900000e+01</td>\n",
       "      <td>9.000000e+00</td>\n",
       "      <td>2.015102e+07</td>\n",
       "      <td>2.017101e+07</td>\n",
       "      <td>2.721690e+05</td>\n",
       "      <td>5.200000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.200000e+01</td>\n",
       "      <td>1.051000e+03</td>\n",
       "      <td>1.300000e+01</td>\n",
       "      <td>2.017013e+07</td>\n",
       "      <td>2.020102e+07</td>\n",
       "      <td>1.085171e+07</td>\n",
       "      <td>5.900000e+01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             target          city            bd  registered_via  \\\n",
       "count  7.375849e+06  7.375849e+06  7.375849e+06    7.375849e+06   \n",
       "mean   5.035420e-01  7.511470e+00  1.753920e+01    6.794075e+00   \n",
       "std    4.999875e-01  6.641632e+00  2.155224e+01    2.275785e+00   \n",
       "min    0.000000e+00  1.000000e+00 -4.300000e+01    3.000000e+00   \n",
       "25%    0.000000e+00  1.000000e+00  0.000000e+00    4.000000e+00   \n",
       "50%    1.000000e+00  5.000000e+00  2.100000e+01    7.000000e+00   \n",
       "75%    1.000000e+00  1.300000e+01  2.900000e+01    9.000000e+00   \n",
       "max    1.000000e+00  2.200000e+01  1.051000e+03    1.300000e+01   \n",
       "\n",
       "       registration_init_time  expiration_date   song_length      language  \n",
       "count            7.375849e+06     7.375849e+06  7.375849e+06  7.375813e+06  \n",
       "mean             2.012810e+07     2.017157e+07  2.451213e+05  1.860810e+01  \n",
       "std              3.017261e+04     3.869916e+03  6.734491e+04  2.117688e+01  \n",
       "min              2.004033e+07     1.970010e+07  1.393000e+03 -1.000000e+00  \n",
       "25%              2.011070e+07     2.017091e+07  2.147260e+05  3.000000e+00  \n",
       "50%              2.013102e+07     2.017093e+07  2.418120e+05  3.000000e+00  \n",
       "75%              2.015102e+07     2.017101e+07  2.721690e+05  5.200000e+01  \n",
       "max              2.017013e+07     2.020102e+07  1.085171e+07  5.900000e+01  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#数字型特征的统计量\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurrences')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#两类分布比较均衡 各占将近50%\n",
    "sns.countplot(data.target)\n",
    "plt.xlabel('target')\n",
    "plt.ylabel('Number of occurrences')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 检查数据质量：异常点、缺省值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "msno                            0\n",
       "song_id                         0\n",
       "source_system_tab           24843\n",
       "source_screen_name         414701\n",
       "source_type                 21535\n",
       "target                          0\n",
       "city                            0\n",
       "bd                              0\n",
       "gender                    2960803\n",
       "registered_via                  0\n",
       "registration_init_time          0\n",
       "expiration_date                 0\n",
       "song_length                     0\n",
       "genre_ids                  118337\n",
       "artist_name                     0\n",
       "composer                  1675125\n",
       "lyricist                  3177973\n",
       "language                       36\n",
       "name                            2\n",
       "isrc                       576394\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.apply(lambda x: sum(x.isnull()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 类别型特征分布情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "source_system_tab属性有9的不同取值，各取值及其出现的次数\n",
      "\n",
      "my library      3684155\n",
      "discover        2178698\n",
      "search           623096\n",
      "radio            476550\n",
      "listen with      212242\n",
      "explore          167882\n",
      "notification       6183\n",
      "settings           2200\n",
      "Name: source_system_tab, dtype: int64\n",
      "\n",
      "source_screen_name属性有21的不同取值，各取值及其出现的次数\n",
      "\n",
      "Local playlist more     3227751\n",
      "Online playlist more    1294324\n",
      "Radio                    474316\n",
      "Album more               419987\n",
      "Search                   298415\n",
      "Artist more              252403\n",
      "Discover Feature         244181\n",
      "Discover Chart           213637\n",
      "Others profile more      201772\n",
      "Discover Genre            82130\n",
      "My library                75970\n",
      "Explore                   72311\n",
      "Unknown                   54160\n",
      "Discover New              15955\n",
      "Search Trends             13632\n",
      "Search Home               13482\n",
      "My library_Search          6451\n",
      "Self profile more           212\n",
      "Concert                      47\n",
      "Payment                      12\n",
      "Name: source_screen_name, dtype: int64\n",
      "\n",
      "source_type属性有13的不同取值，各取值及其出现的次数\n",
      "\n",
      "local-library             2261119\n",
      "online-playlist           1967350\n",
      "local-playlist            1079317\n",
      "radio                      482954\n",
      "album                      477144\n",
      "top-hits-for-artist        423552\n",
      "song                       244670\n",
      "song-based-playlist        210500\n",
      "listen-with                192818\n",
      "topic-article-playlist      11190\n",
      "artist                       3037\n",
      "my-daily-playlist             663\n",
      "Name: source_type, dtype: int64\n",
      "\n",
      "gender属性有3的不同取值，各取值及其出现的次数\n",
      "\n",
      "male      2297173\n",
      "female    2117873\n",
      "Name: gender, dtype: int64\n",
      "\n",
      "genre_ids属性有573的不同取值，各取值及其出现的次数\n",
      "\n",
      "465                      3717210\n",
      "458                      1261169\n",
      "921                       349958\n",
      "1609                      314913\n",
      "444                       243588\n",
      "1259                      181696\n",
      "2022                      152532\n",
      "359                       109482\n",
      "2122                       71806\n",
      "139                        65816\n",
      "451                        63812\n",
      "437                        58454\n",
      "958                        56053\n",
      "786                        43301\n",
      "1616|1609                  42306\n",
      "465|1259                   35352\n",
      "1011                       33490\n",
      "444|1259                   32610\n",
      "921|465                    29743\n",
      "139|125|109                27998\n",
      "2157                       26430\n",
      "726                        21807\n",
      "921|458                    19760\n",
      "465|458                    16925\n",
      "947                        15513\n",
      "691                        15469\n",
      "786|947                    13656\n",
      "1616                       11473\n",
      "465|2022                   10293\n",
      "1152                       10045\n",
      "                          ...   \n",
      "2122|191                       1\n",
      "1609|947                       1\n",
      "921|465|139                    1\n",
      "2022|2215                      1\n",
      "109|921                        1\n",
      "900|958                        1\n",
      "2022|1609|139|125|109          1\n",
      "880|465                        1\n",
      "656|1011                       1\n",
      "465|2122|423                   1\n",
      "940|726                        1\n",
      "388|691                        1\n",
      "388|2122                       1\n",
      "880|786                        1\n",
      "458|2130                       1\n",
      "921|1609|786                   1\n",
      "388|509                        1\n",
      "437|359                        1\n",
      "1609|947|726|2022              1\n",
      "430|691                        1\n",
      "1180|437                       1\n",
      "1609|921                       1\n",
      "1011|2189|367                  1\n",
      "1152|388                       1\n",
      "465|2213|2215                  1\n",
      "2245|242                       1\n",
      "1609|275|1572                  1\n",
      "921|900|893                    1\n",
      "2245                           1\n",
      "921|423                        1\n",
      "Name: genre_ids, Length: 572, dtype: int64\n",
      "\n",
      "artist_name属性有40571的不同取值，各取值及其出现的次数\n",
      "\n",
      "Various Artists                                      303506\n",
      "周杰倫 (Jay Chou)                                       186776\n",
      "五月天 (Mayday)                                         182088\n",
      "林俊傑 (JJ Lin)                                         115325\n",
      "田馥甄 (Hebe)                                           104946\n",
      "aMEI (張惠妹)                                            82799\n",
      "陳奕迅 (Eason Chan)                                      76035\n",
      "玖壹壹                                                   70445\n",
      "G.E.M.鄧紫棋                                             67296\n",
      "BIGBANG                                               61927\n",
      "謝和弦 (R-chord)                                         57040\n",
      "Maroon 5                                              55151\n",
      "A-Lin                                                 52913\n",
      "Eric 周興哲                                              49426\n",
      "蔡依林 (Jolin Tsai)                                      49055\n",
      "蘇打綠 (Sodagreen)                                       47177\n",
      "楊丞琳 (Rainie Yang)                                     46006\n",
      "丁噹 (Della)                                            45762\n",
      "梁靜茹 (Fish Leong)                                      44290\n",
      "The Chainsmokers                                      44215\n",
      "郭靜 (Claire Kuo)                                       42957\n",
      "林宥嘉 (Yoga Lin)                                        41954\n",
      "八三夭 (The Last Day of Summer 831)                      41633\n",
      "蕭敬騰 (Jam Hsiao)                                       40309\n",
      "吳克群 (Kenji Wu)                                        39617\n",
      "韋禮安 (William Wei)                                     39252\n",
      "Alan Walker                                           36781\n",
      "李榮浩                                                   34631\n",
      "周湯豪 (NICKTHEREAL)                                     34614\n",
      "莊心妍                                                   33035\n",
      "                                                      ...  \n",
      "Bob Weir                                                  1\n",
      "Mac Prince                                                1\n",
      "AIKA                                                      1\n",
      "Dj Alex F                                                 1\n",
      "Lance DeSardi                                             1\n",
      "Paul Morrell featuring Vicky Jackson                      1\n",
      "Kenny Black                                               1\n",
      "40 Watt Sun                                               1\n",
      "Juan Lombardo                                             1\n",
      "老九                                                        1\n",
      "Ernesto Cortazar                                          1\n",
      "Cta                                                       1\n",
      "Unic                                                      1\n",
      "Tako                                                      1\n",
      "NoBody                                                    1\n",
      "Isley| Jasper| Isley                                      1\n",
      "Vicky Beeching                                            1\n",
      "Alexandre Azaria                                          1\n",
      "Malcolm McLaren & The World's Famous Supreme Team         1\n",
      "Japa Dollar                                               1\n",
      "DJ Rapture feat. Boobie                                   1\n",
      "周桐同                                                       1\n",
      "Teri Miko                                                 1\n",
      "케이윌| 마마무                                                  1\n",
      "Bankhead                                                  1\n",
      "Ying Blazin                                               1\n",
      "The Royal Soundtrack Band                                 1\n",
      "Colleen Green                                             1\n",
      "High Purity                                               1\n",
      "Soul Archive                                              1\n",
      "Name: artist_name, Length: 40571, dtype: int64\n",
      "\n",
      "composer属性有76035的不同取值，各取值及其出现的次数\n",
      "\n",
      "周杰倫                                                                                                                                                                  201910\n",
      "阿信                                                                                                                                                                    90343\n",
      "林俊傑                                                                                                                                                                   78606\n",
      "陳皓宇                                                                                                                                                                   58837\n",
      "JJ Lin                                                                                                                                                                48089\n",
      "張簡君偉                                                                                                                                                                  43619\n",
      "Eric Chou                                                                                                                                                             42832\n",
      "韋禮安                                                                                                                                                                   39621\n",
      "八三夭 阿璞                                                                                                                                                                32782\n",
      "R-chord                                                                                                                                                               31431\n",
      "怪獸                                                                                                                                                                    31112\n",
      "吳青峰                                                                                                                                                                   30686\n",
      "周湯豪                                                                                                                                                                   29300\n",
      "G.E.M. 鄧紫棋                                                                                                                                                            28698\n",
      "陳小霞                                                                                                                                                                   27632\n",
      "JerryC                                                                                                                                                                26469\n",
      "吳克群                                                                                                                                                                   26111\n",
      "薛之謙                                                                                                                                                                   26110\n",
      "Rocoberry                                                                                                                                                             23444\n",
      "李榮浩                                                                                                                                                                   22816\n",
      "鄭楠                                                                                                                                                                    22814\n",
      "王力宏                                                                                                                                                                   20033\n",
      "徐佳瑩                                                                                                                                                                   18060\n",
      "Yojiro Noda                                                                                                                                                           16903\n",
      "林宥嘉                                                                                                                                                                   16857\n",
      "Kenji Wu                                                                                                                                                              16340\n",
      "蔡健雅                                                                                                                                                                   15706\n",
      "Alan Walker| Jesper Borgen| Anders Froen| Gunnar Greve                                                                                                                15699\n",
      "Eric周興哲                                                                                                                                                               15327\n",
      "孫盛希                                                                                                                                                                   15113\n",
      "                                                                                                                                                                      ...  \n",
      "Bryce Wilson|娃娃臉                                                                                                                                                          1\n",
      "F.Farian| R.Burns| Traditional                                                                                                                                            1\n",
      "JUJU| Jeff Miyahara| RYLL                                                                                                                                                 1\n",
      "Africa Impact Singers                                                                                                                                                     1\n",
      "Ali Tamposi|Christina Aguilera|Nikki Flores|Busbee                                                                                                                        1\n",
      "寂悸+孫偉                                                                                                                                                                     1\n",
      "seohyunill| leesungun                                                                                                                                                     1\n",
      "Verbal Kint                                                                                                                                                               1\n",
      "Kanye West| Noah Goldstein| Mike Dean| Terius Nash| Tyler Bryant| Patrick Reynolds| Malik Yusef| Cydell Young| Joshua \"Southside\" Luellen| J.Williams                     1\n",
      "Simon Green / Erica Wright                                                                                                                                                1\n",
      "Kanye West|Mike Dean|Noah Goldstein|Allen Ritter|Rick Rubin|Scott Mescudi|Leland Wayne|Cydel Young|Jerome Potter|Samuel Griesemer|Chancelor Bennett|T. L. Barrett         1\n",
      "THE☆FUNKS                                                                                                                                                                 1\n",
      "如花如嶽                                                                                                                                                                      1\n",
      "Nasir Jones|Jonathan Davis|Jimmy Heath                                                                                                                                    1\n",
      "Ed Madden|  Gus Edwards                                                                                                                                                   1\n",
      "Alicia Keys| Timothy Mosley| Walter Millsap III| Candice Nelson| Erika Rose                                                                                               1\n",
      "秋楓                                                                                                                                                                        1\n",
      "Dean Stewart| Maxsin Dodson| Renay Phillips                                                                                                                               1\n",
      "Christian Gamboa                                                                                                                                                          1\n",
      "Paul Spatola| Joshua Ansley| Jonathan Wince                                                                                                                               1\n",
      "Brian Littrell|Don Poythress|Brian White|Michael Puryear                                                                                                                  1\n",
      "Easy Mo Bee| Tupac Shakur| Betty Wright| W. Clark| N Durham| O. Harvey Jr.                                                                                                1\n",
      "PASSER| YUICHI| RYO                                                                                                                                                       1\n",
      "Jaakko Salovaara| Perttu Mäkelä| Sini-Maria Makkonen                                                                                                                      1\n",
      "凱莉克萊森|Jimmy Messer|Aben Eubanks                                                                                                                                           1\n",
      "Elektra Jansson-Kilbey|Miranda Jansson-Kilbey|Hannes Netzell|Anders Stenberg|Janne Kask                                                                                   1\n",
      "JOHN WILLIAMS (b. 1932)                                                                                                                                                   1\n",
      "E. Schrody| Erik Schrody                                                                                                                                                  1\n",
      "Christopher Stewart| Terius \"The-Dream\" Nash| Clifford Harris                                                                                                             1\n",
      "Bernard| Smith| Felix Bernard| R. Smith                                                                                                                                   1\n",
      "Name: composer, Length: 76034, dtype: int64\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "lyricist属性有33875的不同取值，各取值及其出现的次数\n",
      "\n",
      "阿信                                                                                          151301\n",
      "方文山                                                                                         124108\n",
      "姚若龍                                                                                          62190\n",
      "周杰倫                                                                                          56235\n",
      "林夕                                                                                           49279\n",
      "韋禮安                                                                                          36291\n",
      "吳青峰                                                                                          34503\n",
      "R-chord                                                                                      33613\n",
      "葛大為                                                                                          32867\n",
      "八三夭 阿璞                                                                                       32388\n",
      "黃婷                                                                                           30337\n",
      "G.E.M. 鄧紫棋                                                                                   28698\n",
      "薛之謙                                                                                          27065\n",
      "吳克群                                                                                          26231\n",
      "陳信延                                                                                          24801\n",
      "施人誠                                                                                          24544\n",
      "徐世珍/吳輝福                                                                                      23479\n",
      "廖建至 洪瑜鴻 陳皓宇                                                                                  21966\n",
      "Yao Ruo Long                                                                                 20667\n",
      "馬嵩惟                                                                                          19738\n",
      "王雅君                                                                                          19345\n",
      "TEDDY| G-DRAGON| T.O.P                                                                       19077\n",
      "Eric Chou| Yi-Wei Wu                                                                         18698\n",
      "藍小邪                                                                                          17616\n",
      "黃偉文                                                                                          17214\n",
      "周湯豪\\崔惟楷                                                                                      16915\n",
      "Ji Hoon                                                                                      15807\n",
      "吳易緯                                                                                          15717\n",
      "鄔裕康                                                                                          15471\n",
      "Kenji Wu                                                                                     15349\n",
      "                                                                                             ...  \n",
      "Yaya                                                                                             1\n",
      "Reel Big Fish                                                                                    1\n",
      "Hooker| Alan Merrill                                                                             1\n",
      "Brad Paisley| Kelly Lovelace                                                                     1\n",
      "豊永利行                                                                                             1\n",
      "Carlos Sadness                                                                                   1\n",
      "張欣瑜\\王磊                                                                                           1\n",
      "小竹正人/PHILLIPS| CHYNNA/WILSON| CARNIE/BALLARD| GLEN                                               1\n",
      "Diego Germini                                                                                    1\n",
      "Carlos Coleman| Marcos Palacios| Tony Russell| Ernest Clark| Kevin Randolph| Uforo Ebong         1\n",
      "張博                                                                                               1\n",
      "UiNA                                                                                             1\n",
      "Tom Hambridge|Jeffrey Steele                                                                     1\n",
      "ハラユカ（Harayuka）                                                                                   1\n",
      "Carole Bayer Sager|David Foster                                                                  1\n",
      "Maurice Williams                                                                                 1\n",
      "Armando C. Perez|José Fernández Diaz|Marc Kinchen                                                1\n",
      "鐘純妍                                                                                              1\n",
      "KEITA|AKIRA|SUNNY BOY|Ryosuke Imai                                                               1\n",
      "Joo Roc of HISPOP                                                                                1\n",
      "Tiziano Ferro                                                                                    1\n",
      "林敏聰                                                                                              1\n",
      "Michael Antony Deighan| Michael Wilshaw                                                          1\n",
      "L                                                                                                1\n",
      "Stuart Gotz                                                                                      1\n",
      "Mickey Furnon                                                                                    1\n",
      "Jason McArthur|飛天火焰樂團                                                                            1\n",
      "Eros Ramazzotti| Adelio Cogliati                                                                 1\n",
      "劉卓輝| 黃家駒| 梁偉文                                                                                    1\n",
      "Mercury                                                                                          1\n",
      "Name: lyricist, Length: 33874, dtype: int64\n",
      "\n",
      "name属性有234112的不同取值，各取值及其出现的次数\n",
      "\n",
      "演員                                                                                                   19260\n",
      "Closer                                                                                               15149\n",
      "Faded                                                                                                15083\n",
      "帥到分手                                                                                                 13973\n",
      "告白氣球                                                                                                 13882\n",
      "你，好不好？ (How Have You Been?)                                                                          13189\n",
      "小幸運 (A little happiness)                                                                             13079\n",
      "Alone                                                                                                12916\n",
      "謝謝妳愛我 (Thanks For Your Love)                                                                         12004\n",
      "讓我留在你身邊                                                                                              11835\n",
      "不為誰而作的歌 (Twilight)                                                                                   11745\n",
      "不該                                                                                                   11732\n",
      "後來的我們 (Here| After| Us)                                                                              11131\n",
      "派對動物 (Party Animal)                                                                                  10791\n",
      "FLY OUT                                                                                              10500\n",
      "好愛好散 (Blue Love Theme)                                                                                9908\n",
      "Don't Let Me Down                                                                                     9833\n",
      "可惜沒如果 (If Only)                                                                                       9532\n",
      "默                                                                                                     9485\n",
      "Let Me Love You                                                                                       9250\n",
      "當你                                                                                                    9195\n",
      "走著走著就散了                                                                                               9073\n",
      "Sugar                                                                                                 9070\n",
      "孤獨是會上癮的 (Addicted To Loneliness)                                                                      9038\n",
      "See You Again                                                                                         8876\n",
      "是我不夠好 (Not Good Enough)                                                                               8845\n",
      "修煉愛情 (Practice Love)                                                                                  8775\n",
      "We Don't Talk Anymore                                                                                 8736\n",
      "Love Yourself                                                                                         8732\n",
      "光年之外                                                                                                  8725\n",
      "                                                                                                     ...  \n",
      "Velho Piano                                                                                              1\n",
      "Sounds of Nature White Noise Sound Effects                                                               1\n",
      "4. Notturno                                                                                              1\n",
      "Final Boarding Call -Interlude-                                                                          1\n",
      "勵志                                                                                                       1\n",
      "Tous pour un (extrait du spectacle « Les 3 Mousquetaires »)                                              1\n",
      "絵巻 (Panorama)                                                                                            1\n",
      "Day Two                                                                                                  1\n",
      "TSUMIKIKUZUSHI (feat. RAW-T| SIMON JAP| G.O| CAZINO & SNUFKIN)                                           1\n",
      "「Attack on Titan: Junior High」Original Drama Dai 3 Wa~Jitsuroku ! No Name!~                              1\n",
      "Pictures at an Exhibition: 9.The Hut on Fowl's Legs (Baba-Yaga)/La Cabane sur des pattes de poule        1\n",
      "Tuna Dreams                                                                                              1\n",
      "Miami (Original Mix)                                                                                     1\n",
      "I'm In You                                                                                               1\n",
      "敗部復活                                                                                                     1\n",
      "Cello Suite No. 3 in C Major| BWV 1009: I. Prelude                                                       1\n",
      "친구보다는 Another Day (feat. G.Na & Dok2) [Korean Version]                                                   1\n",
      "Can You See Him                                                                                          1\n",
      "Monstercat Podcast EP. 134 (Challenge 5 - Showdown)                                                      1\n",
      "離愛不遠 (Li Ai Bu Yuan)                                                                                     1\n",
      "SSAW                                                                                                     1\n",
      "繼續行                                                                                                      1\n",
      "For Her Light                                                                                            1\n",
      "Don't Trust 'Em                                                                                          1\n",
      "Peer Gynt| Op. 46|  I. Morning Mood - \"Morgenstemning\"                                                   1\n",
      "Testify To Love                                                                                          1\n",
      "小副歌                                                                                                      1\n",
      "好先生                                                                                                      1\n",
      "My Friends Tigger & Pooh Theme                                                                           1\n",
      "夜深了 (音樂版)　                                                                                               1\n",
      "Name: name, Length: 234111, dtype: int64\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "isrc属性有269721的不同取值，各取值及其出现的次数\n",
      "\n",
      "TWAG11600306    13973\n",
      "TWK971601308    13293\n",
      "TWA471602002    13189\n",
      "TWD951562101    13079\n",
      "TWA531657203    12004\n",
      "HKJ631603001    11835\n",
      "TWA531576502    11745\n",
      "TWK971601306    11648\n",
      "USQX91601347    11362\n",
      "TWK231610206    11131\n",
      "TWK231680790    10791\n",
      "NOG841549010    10565\n",
      "TWA451512031    10500\n",
      "TWA471410001    10447\n",
      "TWA531658601     9908\n",
      "NOG841617010     9736\n",
      "CNA651500229     9559\n",
      "TWA531480007     9532\n",
      "TWA531398017     9040\n",
      "TWA531612701     9038\n",
      "USQX91600011     8931\n",
      "TWD951676105     8883\n",
      "TWA471698001     8845\n",
      "USAT21502909     8767\n",
      "HKI111600014     8725\n",
      "TWA451601609     8381\n",
      "TWUM71600104     8314\n",
      "HKI111600009     8296\n",
      "USUM71516761     8263\n",
      "USAT21500313     8248\n",
      "                ...  \n",
      "JPPC01501896        1\n",
      "TCABC1131649        1\n",
      "USJI10900639        1\n",
      "ITO101056115        1\n",
      "FRZ811509068        1\n",
      "HKA610300727        1\n",
      "FRY510988901        1\n",
      "TCACB1463274        1\n",
      "GBAYC9602633        1\n",
      "DEU671602564        1\n",
      "TCABY1406950        1\n",
      "JPB671402223        1\n",
      "FR6V80860022        1\n",
      "FRZ209908223        1\n",
      "USUM71604418        1\n",
      "JPPO01200527        1\n",
      "FR6V81046337        1\n",
      "QMBZ91665904        1\n",
      "CA6D21600281        1\n",
      "ROMAY1400005        1\n",
      "FRX871595421        1\n",
      "USFB20604781        1\n",
      "QMBZ91400847        1\n",
      "SEADD0000845        1\n",
      "USWB10803345        1\n",
      "TCACD1592653        1\n",
      "GBCBR9900274        1\n",
      "GBAHT1200238        1\n",
      "DEKL71600085        1\n",
      "GBUM71108666        1\n",
      "Name: isrc, Length: 269720, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "cat_features=['source_system_tab','source_screen_name','source_type','gender','genre_ids','artist_name','composer','lyricist','name','isrc']\n",
    "for col in cat_features:\n",
    "    num_vlaules = len(data[col].unique())\n",
    "    print('\\n%s属性有%d的不同取值，各取值及其出现的次数\\n'% (col,num_vlaules))\n",
    "    print(data[col].value_counts()) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurrences')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#触发事件的类型分布9类\n",
    "sns.countplot(data['source_system_tab'])\n",
    "plt.xlabel('source_system_tab type')\n",
    "plt.ylabel('Number of occurrences')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurrences')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#用户看到的布局的名字分布21类\n",
    "sns.countplot(data['source_screen_name'])\n",
    "plt.xlabel('source_screen_name type')\n",
    "plt.ylabel('Number of occurrences')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurrences')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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K3B36K+A8UisxS6qtjpmZWfuUCYILI+L0ymtiZmbWZmWC4I8lnQDcDCxqJEbEg5XVyszMrA3KBMGtgM8CH6PjdGjk32ZmZv1WmSC4L7Bp8XVKZmZmA0GZFmOmAcOqroiZmVm7lTkSXBf4vaT7WfqaoB+RMDOzfq1MEDyh8lqYmZn1gTLvE7y9HRUxMzNrtzItxswn3Q0KsAIwFFgQEatXWTEzM7OqlTkSXK34W9I+wPaV1cjMzKxNytwdupSI+BV+RtDMzAaAMqdD9yv8HASMouP0qJmZWb9V5u7Q4nsFXweeAvaupDZmZmZtVOaaoN8raGZmA1KnQVDS8V0MFxFxSgX1MTMza5uujgQXtEhbBTgMWAtwEDQzs36t0yAYEac1uiWtBhwJHApcAZzW2XBmZmb9RZfXBCWtCfwHcBBwIbBtRDzfjoqZmZlVratrgt8D9gPOBraKiJfbViszM7M26Oph+a8C7wCOA2ZLeil/5kt6qT3VMzMzq05X1wR73JqMmZlZf9IngU7SU5IekjRV0uSctqakiZKeyN/Dc7oknS5phqTpkrYt5DM29/+EpLGF9O1y/jPysOqqDDMzq6e+PNr7aERsExGj8u9jgUkRsTkwKf8G2APYPH/GAWfBGzftnADsQGrQ+4RCUDsr99sYbnQ3ZZiZWQ0tT6c89ybdgUr+3qeQflEk9wDDJK0H7A5MjIh5+Y7VicDo/N/qEXF3RARwUVNercowM7Ma6qsgGMDNkh6QNC6nrRsRcwDy9zo5fX3g6cKws3JaV+mzWqR3VYaZmdVQmQa0q/DBiJgtaR1goqTfd9GvWqRFL9JLy4F5HMBGG23Uk0HNzKwf6ZMgGBGz8/ezkq4lXdN7RtJ6ETEnn9J8Nvc+C9iwMPgGwOycvktT+m05fYMW/dNFGc31O5v0fCSjRo3ya6MGiEOvHd19T71wwb43VZKvmVWv7UFQ0irAoIiYn7t3A04GrgPGAt/J37/Og1wHHCHpCtJNMC/mIDYB+HbhZpjdgK9FxLz8LOOOwL3AwcAZhbxalWFm1mee+tFfK8l35FFvryTfgaQvjgTXBa7NTy0MAS6LiJsk3Q9cKekwYCawf+7/BmBPYAbwCqn9UnKwOwW4P/d3ckTMy91fAsYDKwE35g+k4NeqDDMzq6G2B8GIeBLYukX6c8CuLdIDOLyTvM4Hzm+RPhnYsmwZZmZWT8vTIxJmZmZt5SBoZma11VePSJgNaJ+89nuV5X39vsdUlrdZ3fhI0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMastB0MzMasvvEzQbAP7pqksry/s3Yw6qLG+zvuYjQTMzqy0HQTMzqy2fDrU3TDhvz0ry3f2wGyrJ18xsWflI0MzMastHgmbWY/tcNamyvH81ZtfK8jZr5iNBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrrVoGQUmjJT0uaYakY/u6PmZm1jdqFwQlDQZ+AuwBvBf4tKT39m2tzMysL9TxfYLbAzMi4kkASVcAewOP9mmtzMza5Jkf311JvuseuVMl+VZJEdHXdWgrSWOA0RHx+fz7s8AOEXFEoZ9xwLj8813A470oam3gb8tYXZfn8gZCeQN53Fxe5zaOiBFvdWXeanU8ElSLtKX2BCLibODsZSpEmhwRo5YlD5fn8gZCeQN53Fxe/1e7a4LALGDDwu8NgNl9VBczM+tDdQyC9wObS9pE0grAgcB1fVwnMzPrA7U7HRoRr0s6ApgADAbOj4hHKihqmU6nujyXN4DKG8jj5vL6udrdGGNmZtZQx9OhZmZmgIOgmZnVWO2DoKTx+dlBJJ37VrQeI+nlLv47UdLRPczvRElHt6proyxJ75B0Ve4+RNItkt7R2zI7qUen41XoZ6Skh0vm1xivQySdWXKY2ySNKvx+Y9wknSzp44X/hkn6f4Xfz0r6QO6+q5tyvi5pF0m/yb9/1Nkwkm7IZS1VXlmSLpc0XdK/93TYXpR1SGO5yL9fy8vRG8tPq/57O27LWNeW07U4X5r6P0rSys3Dd5H/ZZJ+1k0d9mo0rdjLdbfldJP0lKS1O0tvrEetxqHVOt+TsvN/zctBl9u+nqyj3VmW7VFPttfN49iZ2gfBooj4fET0i5ZjmusaEbMjYkyhl/cAnS4ASkrNf6Wm5pZ7EXF8RNxSSBoGFDcCKwPvkiRg526y+3rT76nAg52Uu2dEvNCivG5JejvwgYh4X0T8sOQwvbqhLc/HQ1h6uVgUEY+2WH4aGv33eNyWVU+max63o0jzuHn4zuxGNzcHRsR1EfGd8rV+k2Wabl2NQxfzrMuyWy0H/Wnb11CizofQxTawmNGA+wD/ATycP0cBI4HHgHOAR4CbgZVyv+OBMbn7NmBU7n4Z+BYwDbgHWDenjwCuJj1qcT/wwRblvww8BXwXmAO8Qmp15gDgROBo4BvA34ElwOvAvcCPc79L8vDDgNXz74nAc8CfgXfnun48D/sc8ALpof/jgDNz+gJgIXA7cDFwF/AqcCswhRQoZxX6uyLXf5Vcj7/m/64gBYBXcl4PA4uA3wMPAcfm6XR3rtfC/Ps7Ob9/y9PqZeCJPD0fzvPjaNLCembu91O5bgtJz28+ClwFzMjT/jbgH/PvC3I/fwVOyvPyJOBa4DvAi3naLQR+lafP4sI0nwzMzP+/kL/vytMzgLnArFyvc4E/AjcBf8rzYTowCXia1KrGFXmeTgW+B6wH3JF/Pwx8qMWyMr0wzIeAbfL0mZ7HY3hh2fx2nv5fbZHPOYVxeJa0rO2a59Mz+XNIngev5Wk2JY/nPwOb5uFfznnMz9NoMfAk8Hxx3HKZx+T5Oh04KaeNpJN1ram+/wl8JXf/EPi/3L0rcEnufipP1//N9Xw9fx4lLV+N+flCnmevkpbHW0nLx8w8/CrA9XmYWaRlZkYe9rnc/6dI6+AU4BY61vdD6Fg2TyQtr5sBDxbGZXPggRbjuEueF4vzNG0sFw/nuk4BHqBj/Xspj9944L+AeXl+PJL7uzlP6wCuzNN6BmnZ2AL4S85ncZ7HM/P33/P3icBvgc/kfB/PdVqJpbd9o0nr+zRgUovp0O02sDD/vgvclz/vLE7Hpm3DtJznysBqpHVsaO5n9ZzXUFpsr0l3+Y/P0/Uh4N+BMc3j2Gm86OuAVUEA3C5PiFWAVfMC9P68cG2T+7kS+Ew3QTCAT+Xu/wGOy92XATvn7o2Ax7oIgpeRgtfYvADPBL5P2kD8Hrgs978maeV4AfgH0sb9qbxQjCMt2Nfmup5D2iDfBvyCtDI1ygjSxuwQ0sZvV9IC/izwB1ITcEtIG8R3kPaCN851WIe0sryPtFGcD/xn/m+NXN5iOlaAv+R6rpvrsC+pUfK/AI80xit/r1WYvlOALwMfzvVqDoLDSSt3AKcCpwHnkx5pOSrncXiuw5qkFeqYnP5r0sL/B9LGYWSepgcCX8x5fjPXeQkpSJ2Vu/cgLS8LgSPyPLwS+E0hCL6Yp8X1pGakNgQ+R9o5WDuX93BhOfgq8I3cPRhYrcWy0jzMdOAjuftk4EeFaffTLpb7saRlY3Du9wOk4DyLFHAuKky/2cCX83BLSDsI/5Tn49eAM4Af5el1F/DBFvXcjXTrvEhnlH6T5+lIOlnXmuq7I/DL3H0naSM5FDgB+EJTENw512Ur0kZyUa5rkNabecB5+XvtXLerC8P/c54265HWwU2BFfK8Prew3DXulv88cFpnQTB331oYx283pmeLILiItCEeTNrQT8vdM/N8WC/XbwmwUx6v3wJH5vGbQ0ezZY3xWwK8k6WD4Bl5nO/J02hH0vr6l1yXBcCFhbrdRt7WNQWUEaTlZpOmdbg4HbrdBhbmX2P5P5iOdak4Hdcq9P9NOpbLC4B9cve4wvwYz5uD4HbAxEI+w1qNY2efgXg6dGfg2ohYEBEvA9eQ9rD/FBFTcz8PkBagrrxKWrGb+/84cKakqaSH7FeXtFoneSwELictNNuR9uLXJwW6S4CPSnqatCf0r6SNx3mkjcm6pOB9KB17uJCORhp12Ya0h7cp8FHSyjE///c88GJE/J20Z/4n0gr5Z1JA2Z60ARsv6e85/W2kFfGh3L2JpA9FxIvAjaSN3URSg+PK47Iw12FxnjbnkJuhi4h5uS5bSrqTtMC+HdgiIu4AVszlFG1A2mC/BuxH2sO9JP93cP7ei7SS/AvwBdKe3xakI2dIR70rAT8gBbZfk44eA/hjRDyTu3+b8xJwGPDJPB3emfNplNswK0+LHUhHkRvnslaktfuBQyWdCGwVEfM76Q8ASWuQVuDbc9KFpGWh4RddDL4xafrMIS0XO5Pm+et5uOa8rsnfQUdwGEI6y7AA+ARpp2hF0nLTbLf8mUI6ang36YgIyq1rDwDb5XVnEekswijSunpni/4Xk+bH3aTl8Omc9nPScj+NtOMLacfkgsKwD5GWzZ8Aj0bEkxHxah7Phg2ACZIeIu1UbdGiDkXnkubtYNJR92Wd9DcVeC0iFpOPyHP3EtI6ehdpnRFpuR9COiLdOtdvMGl5XAzMjYhGG57Np0jvJk271UjL3dmk6bQk//8aKSh1Z0fgjoj4Eyy1Dhf1ZBt4eeG7VevaW0q6M0/3g+iY7ueStn3k7wtaDNvwJLCppDMkjSYdUZc2EINgq7ZBYekVeTHdNxTwWuTdiab+BwE7RcQ2+bN+RMyXNEHSVEnndpJfNP3+Kym4nUXacN1L2ogfERGbkWbkyqSVoHH6bmXSUdSOpCO5xrhuTdoDHETag/8YsBZwaeHCcKP8BYXfR5I2PBtFxEr5v9Ui4g+5TtOAUyUdTzpFBGlP/UnSkfFuuQ6NvJea9pIuyCvKjaSjq8mkjXFz4FsTOCD3ezVpYzCHFOAa/b5C2ogMA7YkBfajc34/IB2dNa5dnpf7bZzSu75YN0mb5Gl1HGnFm5v7/Sbp1EvkvH4EfKhwI87iQp27XYZyoP8w6ej4YkkHS9o3LydTizf4lLQg139wIY+T8/gcTApE/0Fa1ndsHq5JcX0YQlreXiUtR1uQTjlG7m5VTwGnFtaDd0bEeS3yXgwMkbRhoc5fjIjGRvlQUiC4k7Qjtxlp3ha9n471bms65uvC/K1c/8Wk4L8DaZmDdMR2JfBL0g7O+/Py3OwM0pHOViy93HXmatLZg38inQp9TtIOhXHcK/fXvN43vI109mU8afl4kXRq8FXSEXHk8VyVtIP8WFNeg/JnQ9L8eTdpOd+YtDNwVGHaNBSX384U1+fO9GQbGJ10N4wnbfO2Il3KeBtARPwOGCnpI8DgiOj0ZruIeJ60DbyNdJaos21wpyMz0NwB7CNpZUmrkE7Ttdqz7K2bSRt0ACRtAxARu+cF4vOFfoeS9hIPJO35NjaIfyCtaKuQZtg5+b/BwIqShpIWhjVZeg/oFdJ1w8mkUylTSRuwQXRs6N4H/B9pgT+GtLf5bmAT0l79YNJpmvtJpz4WAs9J2i/Xhxw4g3Qt7vvAtnQciZ5LOrI4UNJWeRxXKEybf6NjxftqRGyT6z0npx+Uy9g5l72QdJrnF7nfBaQdhI1IQQ7g06SjtnNJ1zFvIW0cFpA2uKuSNkgNL5EC2255/Lch7WSItKe8ce7vNtJR+QjSafOzc/cTuV73AXdGxGSWdhcdF9wPyv1C2mi9sUcsaWPg2Yg4hxSYt42Iawsbj6XyzUeZz0v6UE76LOnsAU39LS7kcTwpcC/K020iaT5vTjoCG9KU13xar/fDSfNpdeBnpHm+cs5zy+ZxI51N+JykVfO4ri9pnRb5Nur8dKHOjTsy7yDN4ztI6+gXgamFnc+GwTmPVyS9m3RKupW5pCPDK/PRFqTAuidwPOmyhoAdCuvY0NzfGqR1E9Kp5S5FxMI8Dc4ir6MRcW9hHBtNMW4NDMs3oY0A1slHj4NIy+1TpGC1Bmmar0gK5PeTzpoMJZ0ufQFYS9JapJ3ij9Bx5mcyKZg0riv+inQ6fDCdB/Pm+dlwNw3qk7YAAAYMSURBVPCRvGOFpDVb9NOTbeABhe9W729aDZiT58dBTf9dRDqC7OookHyX7aCIuBr4b9J0hM7HcSkDrtm0iHhQ0njSBgzShvP5t7CIrwA/kTSdNP3uIK28rcwgXZf7Oen0zX+SNuJ/Ja0E2+Tu10gL7pakjcFrpCC3KWkhOLWT/M8hrSB/JZ26gnTDzZqkoHsZHadXHiddW9uUtOc1W9L3SHviC+g4GoJ07WU90l70QuBLEfGqpEWkjeRepFOhN5EC2PHAKaSN6GPAzvmo7gbSXZb/neswPE+TPUl7r63abD0R+GnOawPSqaDnSBub10gr9nURMU3SFNLdb3OB35H2rCEt+Jvlur5Gur63LWmj8b38vZi0szA0d5+Uh72DNI8XkE77NAJc0VdIG57zSBuxeQD5aOB3So+I3Ei6UH+MpEYdDm6RV7OxwM+UbvV/ko5TQp3K0+IvpOV8UR6/q0nL0g15nO4hBbdZpBsfbpW0fSGbt5OC3nGkDXHjKOsFYHfShvmexrhFxDGS3gPcnW625WXSDRdljjYa7iQtr3dHxAJJC2m9w3oD8L38/59JR02t/CB/dmlK34qO+b6AtJ7dQgo0e0m6lbTc/TJPx3tIO43duZR0yv7mLvq5m7QsvkK6D2Ai6QzLMNI6eTRph2ox6QazIF0rn0BalzYjBcvFpHXpdtK241yWfsXbAaRtwSqka5p35fF9Is+z5mA4nrSc/Z3CacqImKv0KrlrcuB+lnRqvKgn28AVJd2b6/zpFv83tg1/Ju1oF4PWpaSzM5e3GK5ofeCCwt3uX2s1jvnS0Jt1d9HQn17foPMUsPYyDD8GuLibflYEhuTunUh70VWO09HAKcsw/G2UuFBN000YhfRRpCOzMmWdCRxWor9dyBfs6/5p9/JUQf1LLx9vUXldrg9ll62u+iPdl7BrX0/bXk6fyreBb8VnwB0JDgSSziCd3tuzm143Aq7Me0Cvkk5FVlWna0l7pR+rqoxuyj8W+BJvPmXSqt/GbedfrbpeA0zblqe3Wk+Wj7eovErXB6UH5O8DpkXEpCrKWJ71YBu47GXliGtmZlY7A/HGGDMzs1IcBM3MrLYcBM0GKJVsQNiszhwEzZYzvW0gu4VDKNOAsFmNOQiaLQNJq0i6XtI0pVffHJDTd5U0RdJDks6XtGJOf+MVOpJGSbotd58o6WxJNwMX5VZhvp+Hny7py7m/7STdLumB3ELHep3UawzpkYFLcysen8x3NDb+/4Ska3L3y5JOk/SgpEmSRuT0zSTdlMu6Mz+objagOAiaLZvRwOyI2DoitgRukvQ20oO6B0RqDmoI6fb97mwH7B0R/0pqNHgT4P0R8T5SMBtKat5rTERsR2r84FutMoqIq0gP9B8UqSWeG4D3NAIcS7fHuArprQjbkh7GPiGnn01q0Hg70jNxPy01Rcz6EQdBs2XzEPBxSd9VR2Pj7yI1Iv2H3E9z49WduS46WrX4OPCziHgd3mjI+F2k1k4m5hZ5jiO1qtOtSM9CXQx8Jj+DthMd7WsuoaNx7ktILf6sSmp665e5rJ+TWhEyG1D8sLzZMoiIP0jajvRQ76n5dGar5uAaXqdj57O5KatiQ9etGjIW6TVVrVrjL+MC0rv5FpJeY/R6J/1FruML+SjSbMDykaDZMsh3X74SEZfQ0dj470kt4DdeyVRsCPsp0mlPSG09duZm4IuNm2RyQ8aPAyMk7ZTThkrq6pU/SzUgHBGzSW3SHkc6XdswiNREFaQ3Fvw2Il4C/iRp/1yWJG3dRVlm/ZKDoNmy2Qq4L58y/AbwzUhvGDiUdCrxIdLpxsabE04Cfqz0fsWuGps+l/SOv+mSpgH/GukdeGOA7+a0qaRTlp0ZT2pAeKqklXLapcDTEfFoob8FwBa5ubmPkV7mC6kJssNyWY+Q3iNpNqC42TSzGpF0JjAlOt79h6SXI2LVPqyWWZ9xEDSriULD4p+IiEWFdAdBqy0HQbN+TtJPgA82Jf84Irp8GamZOQiamVmN+cYYMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrLQdBMzOrrf8P5HNQnq5b+9cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#用户播放音乐入口类型13类\n",
    "sns.countplot(data['source_type'])\n",
    "plt.xlabel('source_type ')\n",
    "plt.ylabel('Number of occurrences')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurrences')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#类别型特征性别\n",
    "sns.countplot(data['gender'])\n",
    "plt.xlabel('source_type ')\n",
    "plt.ylabel('Number of occurrences')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Number of occurrences')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data['genre_ids'])\n",
    "plt.xlabel('source_type ')\n",
    "plt.ylabel('Number of occurrences')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可见用户id和歌曲id特征取值有一部分较少，较离散"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### msno，song_id\n",
    "LightGBM对类别特征建立直方图，当特征取值数目超过max_bin,会去掉样本数目少的类别\n",
    "统计该特征下每一种离散出现的次数，并从高到低排序，并过滤掉出现次数较少的特征值，\n",
    "然后为每一个特征值，建立一个bin容器，对于在bin容器内出现次数较少的特征值直接过滤掉\n",
    "，不建立bin容器"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#genre_ids 573种   371 370\n",
    "#artist_name 40571种 6503\n",
    "#composer 76035      9467\n",
    "#lyricist 33875      5693\n",
    "#name 234112         10089\n",
    "#isrc 269721         9354\n",
    "\n",
    "cat_features =['genre_ids','artist_name','composer','lyricist','name']\n",
    "rare_thresholds = [10,40,40,40,100]\n",
    "j=0\n",
    "for col in cat_features:\n",
    "    #每个取值的样本数目\n",
    "    #print('col',col)\n",
    "    value_counts_col=data[col].value_counts(dropna=False)\n",
    "    #print('value_counts_col',value_counts_col)\n",
    "    #样本数目小于阈值的取值为稀有取值\n",
    "    #print('j=',j)  \n",
    "    #print('arej=',rare_thresholds[j])  \n",
    "       \n",
    "    rare_threshold = rare_thresholds[j]\n",
    "    #print('rare_threshold',rare_threshold)    \n",
    "    value_counts_rare = list(value_counts_col[value_counts_col< rare_threshold].index)\n",
    "    #稀有值合并为others\n",
    "    rare_index = data[col].isin(value_counts_rare)\n",
    "    data.loc[data[col].isin(value_counts_rare),col]=\"Others\"\n",
    "    j = j+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "source_system_tab属性有9的不同取值，各取值及其出现的次数\n",
      "\n",
      "my library      3684155\n",
      "discover        2178698\n",
      "search           623096\n",
      "radio            476550\n",
      "listen with      212242\n",
      "explore          167882\n",
      "notification       6183\n",
      "settings           2200\n",
      "Name: source_system_tab, dtype: int64\n",
      "\n",
      "source_screen_name属性有21的不同取值，各取值及其出现的次数\n",
      "\n",
      "Local playlist more     3227751\n",
      "Online playlist more    1294324\n",
      "Radio                    474316\n",
      "Album more               419987\n",
      "Search                   298415\n",
      "Artist more              252403\n",
      "Discover Feature         244181\n",
      "Discover Chart           213637\n",
      "Others profile more      201772\n",
      "Discover Genre            82130\n",
      "My library                75970\n",
      "Explore                   72311\n",
      "Unknown                   54160\n",
      "Discover New              15955\n",
      "Search Trends             13632\n",
      "Search Home               13482\n",
      "My library_Search          6451\n",
      "Self profile more           212\n",
      "Concert                      47\n",
      "Payment                      12\n",
      "Name: source_screen_name, dtype: int64\n",
      "\n",
      "source_type属性有13的不同取值，各取值及其出现的次数\n",
      "\n",
      "local-library             2261119\n",
      "online-playlist           1967350\n",
      "local-playlist            1079317\n",
      "radio                      482954\n",
      "album                      477144\n",
      "top-hits-for-artist        423552\n",
      "song                       244670\n",
      "song-based-playlist        210500\n",
      "listen-with                192818\n",
      "topic-article-playlist      11190\n",
      "artist                       3037\n",
      "my-daily-playlist             663\n",
      "Name: source_type, dtype: int64\n",
      "\n",
      "gender属性有3的不同取值，各取值及其出现的次数\n",
      "\n",
      "male      2297173\n",
      "female    2117873\n",
      "Name: gender, dtype: int64\n",
      "\n",
      "genre_ids属性有371的不同取值，各取值及其出现的次数\n",
      "\n",
      "465                       3717210\n",
      "458                       1261169\n",
      "921                        349958\n",
      "1609                       314913\n",
      "444                        243588\n",
      "1259                       181696\n",
      "2022                       152532\n",
      "359                        109482\n",
      "2122                        71806\n",
      "139                         65816\n",
      "451                         63812\n",
      "437                         58454\n",
      "958                         56053\n",
      "786                         43301\n",
      "1616|1609                   42306\n",
      "465|1259                    35352\n",
      "1011                        33490\n",
      "444|1259                    32610\n",
      "921|465                     29743\n",
      "139|125|109                 27998\n",
      "2157                        26430\n",
      "726                         21807\n",
      "921|458                     19760\n",
      "465|458                     16925\n",
      "947                         15513\n",
      "691                         15469\n",
      "786|947                     13656\n",
      "1616                        11473\n",
      "465|2022                    10293\n",
      "1152                        10045\n",
      "                           ...   \n",
      "1965                           13\n",
      "275|1572|829                   12\n",
      "1152|359                       12\n",
      "465|2122|109                   12\n",
      "958|2022                       12\n",
      "786|947|958                    12\n",
      "786|1259                       12\n",
      "1609|958                       12\n",
      "712                            12\n",
      "444|958                        12\n",
      "94|95                          11\n",
      "1609|139|125|109               11\n",
      "1152|873|947                   11\n",
      "2022|786                       11\n",
      "1609|940|2086                  11\n",
      "1609|2122|958                  11\n",
      "359|139                        11\n",
      "252                            11\n",
      "2122|947|726                   11\n",
      "1162                           11\n",
      "1988|430                       11\n",
      "921|893                        11\n",
      "921|1259                       11\n",
      "1152|873|726|958               11\n",
      "388|465                        10\n",
      "947|2022|2122|1259|958         10\n",
      "1609|1969|2100                 10\n",
      "798|786                        10\n",
      "1180|2219                      10\n",
      "1117                           10\n",
      "Name: genre_ids, Length: 370, dtype: int64\n",
      "\n",
      "artist_name属性有6503的不同取值，各取值及其出现的次数\n",
      "\n",
      "Various Artists                                                                                            303506\n",
      "Others                                                                                                     205133\n",
      "周杰倫 (Jay Chou)                                                                                             186776\n",
      "五月天 (Mayday)                                                                                               182088\n",
      "林俊傑 (JJ Lin)                                                                                               115325\n",
      "田馥甄 (Hebe)                                                                                                 104946\n",
      "aMEI (張惠妹)                                                                                                  82799\n",
      "陳奕迅 (Eason Chan)                                                                                            76035\n",
      "玖壹壹                                                                                                         70445\n",
      "G.E.M.鄧紫棋                                                                                                   67296\n",
      "BIGBANG                                                                                                     61927\n",
      "謝和弦 (R-chord)                                                                                               57040\n",
      "Maroon 5                                                                                                    55151\n",
      "A-Lin                                                                                                       52913\n",
      "Eric 周興哲                                                                                                    49426\n",
      "蔡依林 (Jolin Tsai)                                                                                            49055\n",
      "蘇打綠 (Sodagreen)                                                                                             47177\n",
      "楊丞琳 (Rainie Yang)                                                                                           46006\n",
      "丁噹 (Della)                                                                                                  45762\n",
      "梁靜茹 (Fish Leong)                                                                                            44290\n",
      "The Chainsmokers                                                                                            44215\n",
      "郭靜 (Claire Kuo)                                                                                             42957\n",
      "林宥嘉 (Yoga Lin)                                                                                              41954\n",
      "八三夭 (The Last Day of Summer 831)                                                                            41633\n",
      "蕭敬騰 (Jam Hsiao)                                                                                             40309\n",
      "吳克群 (Kenji Wu)                                                                                              39617\n",
      "韋禮安 (William Wei)                                                                                           39252\n",
      "Alan Walker                                                                                                 36781\n",
      "李榮浩                                                                                                         34631\n",
      "周湯豪 (NICKTHEREAL)                                                                                           34614\n",
      "                                                                                                            ...  \n",
      "Kurt Masur                                                                                                     40\n",
      "Nera                                                                                                           40\n",
      "Big Freedia                                                                                                    40\n",
      "French Electro Connection                                                                                      40\n",
      "Susan McRae                                                                                                    40\n",
      "The Kinks                                                                                                      40\n",
      "王羚柔                                                                                                            40\n",
      "KOTOKO                                                                                                         40\n",
      "Menace Beach                                                                                                   40\n",
      "Soloists/Scottish Chamber Orchestra/Sir Charles Mackerras                                                      40\n",
      "Gentle Bones                                                                                                   40\n",
      "Waka Flocka Flame                                                                                              40\n",
      "Original Cast Recording                                                                                        40\n",
      "Hiatus                                                                                                         40\n",
      "Brigitte Fassbaender/Erik Werba/Wolfgang Sawallisch/Chor der Bayerischen Staatsoper M?/Capella Bavariae        40\n",
      "György Sebök|János Starker                                                                                     40\n",
      "馮偉傑                                                                                                            40\n",
      "New Anime Revolution                                                                                           40\n",
      "ZZ Ward                                                                                                        40\n",
      "ジョゼ                                                                                                            40\n",
      "A.R. Rahman & The Pussycat Dolls                                                                               40\n",
      "Modestep| Trolley Snatcha                                                                                      40\n",
      "Cafe Relax at HOME・・・                                                                                          40\n",
      "ZZ Top                                                                                                         40\n",
      "The Merry Christmas Players                                                                                    40\n",
      "Topic                                                                                                          40\n",
      "Timmy Trumpet| Savage| Timmy Trumpet| Savage                                                                   40\n",
      "Lady Bee                                                                                                       40\n",
      "ヨウヘイ                                                                                                           40\n",
      "Seo Inguk| VIXX| Park JungA| Park Yunha                                                                        40\n",
      "Name: artist_name, Length: 6503, dtype: int64\n",
      "\n",
      "composer属性有9467的不同取值，各取值及其出现的次数\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Others                                                                                                                                                  370596\n",
      "周杰倫                                                                                                                                                     201910\n",
      "阿信                                                                                                                                                       90343\n",
      "林俊傑                                                                                                                                                      78606\n",
      "陳皓宇                                                                                                                                                      58837\n",
      "JJ Lin                                                                                                                                                   48089\n",
      "張簡君偉                                                                                                                                                     43619\n",
      "Eric Chou                                                                                                                                                42832\n",
      "韋禮安                                                                                                                                                      39621\n",
      "八三夭 阿璞                                                                                                                                                   32782\n",
      "R-chord                                                                                                                                                  31431\n",
      "怪獸                                                                                                                                                       31112\n",
      "吳青峰                                                                                                                                                      30686\n",
      "周湯豪                                                                                                                                                      29300\n",
      "G.E.M. 鄧紫棋                                                                                                                                               28698\n",
      "陳小霞                                                                                                                                                      27632\n",
      "JerryC                                                                                                                                                   26469\n",
      "吳克群                                                                                                                                                      26111\n",
      "薛之謙                                                                                                                                                      26110\n",
      "Rocoberry                                                                                                                                                23444\n",
      "李榮浩                                                                                                                                                      22816\n",
      "鄭楠                                                                                                                                                       22814\n",
      "王力宏                                                                                                                                                      20033\n",
      "徐佳瑩                                                                                                                                                      18060\n",
      "Yojiro Noda                                                                                                                                              16903\n",
      "林宥嘉                                                                                                                                                      16857\n",
      "Kenji Wu                                                                                                                                                 16340\n",
      "蔡健雅                                                                                                                                                      15706\n",
      "Alan Walker| Jesper Borgen| Anders Froen| Gunnar Greve                                                                                                   15699\n",
      "Eric周興哲                                                                                                                                                  15327\n",
      "                                                                                                                                                         ...  \n",
      "Joel Berghult| Fatima Larsson| Richard Andersson                                                                                                            40\n",
      "Chinese Lyrics by ZHOUMI (周觅) Daniel Caesar / Ludwig Lindell / Olof Lindskog / Casper                                                                       40\n",
      "Yang| Jae Sun / Yoon| Young Jun                                                                                                                             40\n",
      "Gwon Soonil|  Jo HyunAh                                                                                                                                     40\n",
      "周巽光                                                                                                                                                         40\n",
      "John Stephens| Jessyca Wilson| James B. Cobb| Jr.| Buddy Buie| William Adams                                                                                40\n",
      "Mattias Larsen| Robin Fredriksson| Julia Michaels| Justin Tranter| Sandy Chila                                                                              40\n",
      "A. van Buuren| B. De Goeij| R. van de Corput                                                                                                                40\n",
      "T-SK/SIRIUS/Fabrice Haddad                                                                                                                                  40\n",
      "彭佳慧                                                                                                                                                         40\n",
      "Etta James| Tim Bergling| Ash Pournouri| Leroy Kirkland| Pearl Woods                                                                                        40\n",
      "Fu Ming Chen                                                                                                                                                40\n",
      "Fred Mollin| M. Johnson                                                                                                                                     40\n",
      "黃家駒| 劉卓輝                                                                                                                                                    40\n",
      "Kirk Franklin                                                                                                                                               40\n",
      "Daniel Fält| Christopher Nissen| Marcus Winther-John                                                                                                        40\n",
      "ヨウヘイ                                                                                                                                                        40\n",
      "George Gordy| Allen Story| Anna Gaye                                                                                                                        40\n",
      "Davor Vulama / Jennifer Lee Hershman                                                                                                                        40\n",
      "Nguyễn Hoàng Duy                                                                                                                                            40\n",
      "Adam Dyment| Hal Ritson| Timucin Fabian Kwong Wah Aluo| James Norton                                                                                        40\n",
      "Sidney Lippman| Sylvia Dee                                                                                                                                  40\n",
      "Jordan Orvash| Jamahl Listenbee| Maureen Ann McDonald| Francesca Richard| Andre Smith| Stacy Ferguson| Alexander Scott| Andrea Martin| Kamaal Fareed        40\n",
      "Adam Englefield|Jacob Manson|A Pignagnoli|D Riva|Emenike                                                                                                    40\n",
      "A-Lin，游政豪                                                                                                                                                   40\n",
      "舍予                                                                                                                                                          40\n",
      "Soo Yoon Song| Jae Ho Han Jae Ho| Seung Soo Kim Seung Su| Woo Dong| Hoya                                                                                    40\n",
      "藤原 基央                                                                                                                                                       40\n",
      "玉置浩二 (Koji Tamaki)                                                                                                                                          40\n",
      "James Morgan| Juliette Pochin                                                                                                                               40\n",
      "Name: composer, Length: 9466, dtype: int64\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "lyricist属性有5693的不同取值，各取值及其出现的次数\n",
      "\n",
      "Others                                                                                                   178297\n",
      "阿信                                                                                                       151301\n",
      "方文山                                                                                                      124108\n",
      "姚若龍                                                                                                       62190\n",
      "周杰倫                                                                                                       56235\n",
      "林夕                                                                                                        49279\n",
      "韋禮安                                                                                                       36291\n",
      "吳青峰                                                                                                       34503\n",
      "R-chord                                                                                                   33613\n",
      "葛大為                                                                                                       32867\n",
      "八三夭 阿璞                                                                                                    32388\n",
      "黃婷                                                                                                        30337\n",
      "G.E.M. 鄧紫棋                                                                                                28698\n",
      "薛之謙                                                                                                       27065\n",
      "吳克群                                                                                                       26231\n",
      "陳信延                                                                                                       24801\n",
      "施人誠                                                                                                       24544\n",
      "徐世珍/吳輝福                                                                                                   23479\n",
      "廖建至 洪瑜鴻 陳皓宇                                                                                               21966\n",
      "Yao Ruo Long                                                                                              20667\n",
      "馬嵩惟                                                                                                       19738\n",
      "王雅君                                                                                                       19345\n",
      "TEDDY| G-DRAGON| T.O.P                                                                                    19077\n",
      "Eric Chou| Yi-Wei Wu                                                                                      18698\n",
      "藍小邪                                                                                                       17616\n",
      "黃偉文                                                                                                       17214\n",
      "周湯豪\\崔惟楷                                                                                                   16915\n",
      "Ji Hoon                                                                                                   15807\n",
      "吳易緯                                                                                                       15717\n",
      "鄔裕康                                                                                                       15471\n",
      "                                                                                                          ...  \n",
      "Chansung Hwang| Taecyeon a.k.a TY                                                                            40\n",
      "John Stephens| Jessyca Wilson| James B. Cobb| Jr.| Buddy Buie| William Adams                                 40\n",
      "Cali                                                                                                         40\n",
      "Yang Kefca                                                                                                   40\n",
      "Conan| Loco                                                                                                  40\n",
      "羅宇軒                                                                                                          40\n",
      "伍貳柒\\陳靜楠                                                                                                      40\n",
      "Chan Mi (AOA)| Cho A  (AOA)| Hye Jeong (AOA)| Ji Min (AOA)| Mia A (AOA)| Seol Hyun (AOA)| Yu Na (AOA)        40\n",
      "海狗                                                                                                           40\n",
      "加藤登紀子                                                                                                        40\n",
      "Ryu                                                                                                          40\n",
      "Ryeowook / G-high / Park| Asher / Song| Si Yun                                                               40\n",
      "Eric Nam/Pae Su Jung/Kim Bo A of SPICA                                                                       40\n",
      "Jane Zhang| Chen-Mao Yu| Siling Na                                                                           40\n",
      "HILL| PATTY SMITH                                                                                            40\n",
      "Liao Ying-Ru| Stefanie Sun| Sun Stefanie                                                                     40\n",
      "Joel Berghult| Fatima Larsson| Richard Andersson / 改編詞：MP魔幻力量鼓鼓(GL)                                          40\n",
      "Curtis Mayfield                                                                                              40\n",
      "林憶蓮 / 李焯雄                                                                                                    40\n",
      "吳夢奇                                                                                                          40\n",
      "さだまさし                                                                                                        40\n",
      "文有希                                                                                                          40\n",
      "羅志祥 / Wonderful                                                                                              40\n",
      "Carolyn Leigh                                                                                                40\n",
      "Armando C. Perez|Eric Frederic|Tom Peyton|Joe Spargur|Andreas Schuller|Ilsey Juber                           40\n",
      "Korean Lyrics by Chung| Joo Hee (12.5%) Andreas Oberg / Simon Petren / Maja Keuc / Kim| One                  40\n",
      "李俊                                                                                                           40\n",
      "Gwon Soonil|  Jo HyunAh                                                                                      40\n",
      "YORKE.                                                                                                       40\n",
      "Yoon Do Hyun| Lee Jang Mi                                                                                    40\n",
      "Name: lyricist, Length: 5692, dtype: int64\n",
      "\n",
      "name属性有10089的不同取值，各取值及其出现的次数\n",
      "\n",
      "Others                                     1615727\n",
      "演員                                           19260\n",
      "Closer                                       15149\n",
      "Faded                                        15083\n",
      "帥到分手                                         13973\n",
      "告白氣球                                         13882\n",
      "你，好不好？ (How Have You Been?)                  13189\n",
      "小幸運 (A little happiness)                     13079\n",
      "Alone                                        12916\n",
      "謝謝妳愛我 (Thanks For Your Love)                 12004\n",
      "讓我留在你身邊                                      11835\n",
      "不為誰而作的歌 (Twilight)                           11745\n",
      "不該                                           11732\n",
      "後來的我們 (Here| After| Us)                      11131\n",
      "派對動物 (Party Animal)                          10791\n",
      "FLY OUT                                      10500\n",
      "好愛好散 (Blue Love Theme)                        9908\n",
      "Don't Let Me Down                             9833\n",
      "可惜沒如果 (If Only)                               9532\n",
      "默                                             9485\n",
      "Let Me Love You                               9250\n",
      "當你                                            9195\n",
      "走著走著就散了                                       9073\n",
      "Sugar                                         9070\n",
      "孤獨是會上癮的 (Addicted To Loneliness)              9038\n",
      "See You Again                                 8876\n",
      "是我不夠好 (Not Good Enough)                       8845\n",
      "修煉愛情 (Practice Love)                          8775\n",
      "We Don't Talk Anymore                         8736\n",
      "Love Yourself                                 8732\n",
      "                                            ...   \n",
      "Circus Monkey (Circus Monkey)                  100\n",
      "愛的路上我和你                                        100\n",
      "漫漫長夜                                           100\n",
      "chAngE (第三張單曲，動畫【死神BLEACH】片頭曲)                 100\n",
      "至少我有我                                          100\n",
      "Neon                                           100\n",
      "任性 - 電影: 雙城計中計 主题曲                             100\n",
      "狠不下心                                           100\n",
      "卡農 (Pachabel's Canon )                         100\n",
      "路過的新娘                                          100\n",
      "愧                                              100\n",
      "後天 (After Day)                                 100\n",
      "紙箋                                             100\n",
      "Insane Dream                                   100\n",
      "只要有你 (feat. Kim Jin Pyo)                       100\n",
      "曠野寄情                                           100\n",
      "記得。愛                                           100\n",
      "給愛人                                            100\n",
      "Good Morning| Hard City (三立<我的自由年代>片頭曲)        100\n",
      "如煙 [Live at 中山足球場]                             100\n",
      "挑撥                                             100\n",
      "殺死那個石家莊人                                       100\n",
      "Breakfast on the Morning Tram                  100\n",
      "十七歲我是女生的溫柔                                     100\n",
      "重愛輕友                                           100\n",
      "不如跳舞                                           100\n",
      "壞天氣好心情                                         100\n",
      "A Dream Is A Wish Your Heart Makes             100\n",
      "未完成的愛                                          100\n",
      "再見我的愛人                                         100\n",
      "Name: name, Length: 10089, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "cat_features=['source_system_tab','source_screen_name','source_type','gender','genre_ids','artist_name','composer','lyricist','name']\n",
    "for col in cat_features:\n",
    "    num_vlaules = len(data[col].unique())\n",
    "    print('\\n%s属性有%d的不同取值，各取值及其出现的次数\\n'% (col,num_vlaules))\n",
    "    print(data[col].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "source_system_tab <class 'str'>\n",
      "source_screen_name <class 'str'>\n",
      "source_type <class 'str'>\n",
      "gender <class 'str'>\n",
      "genre_ids <class 'str'>\n",
      "artist_name <class 'str'>\n",
      "composer <class 'str'>\n",
      "lyricist <class 'str'>\n",
      "name <class 'str'>\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "le = LabelEncoder()\n",
    "feats_to_encode=['source_system_tab','source_screen_name','source_type','gender','genre_ids','artist_name','composer','lyricist','name']\n",
    "for col in feats_to_encode:\n",
    "    print(col,type(col))\n",
    "    data[col] = le.fit_transform(data[col].astype(str))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### #最终数据样式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>msno</th>\n",
       "      <th>song_id</th>\n",
       "      <th>source_system_tab</th>\n",
       "      <th>source_screen_name</th>\n",
       "      <th>source_type</th>\n",
       "      <th>target</th>\n",
       "      <th>city</th>\n",
       "      <th>bd</th>\n",
       "      <th>gender</th>\n",
       "      <th>registered_via</th>\n",
       "      <th>registration_init_time</th>\n",
       "      <th>expiration_date</th>\n",
       "      <th>song_length</th>\n",
       "      <th>genre_ids</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>composer</th>\n",
       "      <th>lyricist</th>\n",
       "      <th>language</th>\n",
       "      <th>name</th>\n",
       "      <th>isrc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>11</td>\n",
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       "      <td>15</td>\n",
       "      <td>18</td>\n",
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       "      <td>20151220</td>\n",
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       "      <td>3032</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1334</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>xbodnNBaLMyqqI7uFJlvHOKMJaizuWo/BB/YHZICcKo=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>20120804</td>\n",
       "      <td>20171004</td>\n",
       "      <td>206471</td>\n",
       "      <td>183</td>\n",
       "      <td>469</td>\n",
       "      <td>1449</td>\n",
       "      <td>3032</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1334</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>s0ndDsjI79amU0RBiullFN8HRz9HjE++34jGNa7zJ/s=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>20110808</td>\n",
       "      <td>20170917</td>\n",
       "      <td>206471</td>\n",
       "      <td>183</td>\n",
       "      <td>469</td>\n",
       "      <td>1449</td>\n",
       "      <td>3032</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1334</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Vw4Umh6/qlsJDC/XMslyAxVvRgFJGHr53yb/nrmY1DU=</td>\n",
       "      <td>BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>20070323</td>\n",
       "      <td>20170915</td>\n",
       "      <td>206471</td>\n",
       "      <td>183</td>\n",
       "      <td>469</td>\n",
       "      <td>1449</td>\n",
       "      <td>3032</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1334</td>\n",
       "      <td>GBUM71602854</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           msno  \\\n",
       "0  FGtllVqz18RPiwJj/edr2gV78zirAiY/9SmYvia+kCg=   \n",
       "1  pouJqjNRmZOnRNzzMWWkamTKkIGHyvhl/jo4HgbncnM=   \n",
       "2  xbodnNBaLMyqqI7uFJlvHOKMJaizuWo/BB/YHZICcKo=   \n",
       "3  s0ndDsjI79amU0RBiullFN8HRz9HjE++34jGNa7zJ/s=   \n",
       "4  Vw4Umh6/qlsJDC/XMslyAxVvRgFJGHr53yb/nrmY1DU=   \n",
       "\n",
       "                                        song_id  source_system_tab  \\\n",
       "0  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=                  1   \n",
       "1  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=                  0   \n",
       "2  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=                  3   \n",
       "3  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=                  3   \n",
       "4  BBzumQNXUHKdEBOB7mAJuzok+IJA1c2Ryg/yzTF6tik=                  3   \n",
       "\n",
       "   source_screen_name  source_type  target  city  bd  gender  registered_via  \\\n",
       "0                   7            7       1     1   0       2               7   \n",
       "1                  11            7       0    15  18       1               4   \n",
       "2                   8            3       1     1   0       2               7   \n",
       "3                   8            3       1     5  21       0               9   \n",
       "4                   8            3       0     6  33       0               9   \n",
       "\n",
       "   registration_init_time  expiration_date  song_length  genre_ids  \\\n",
       "0                20120102         20171005       206471        183   \n",
       "1                20151220         20170930       206471        183   \n",
       "2                20120804         20171004       206471        183   \n",
       "3                20110808         20170917       206471        183   \n",
       "4                20070323         20170915       206471        183   \n",
       "\n",
       "   artist_name  composer  lyricist  language  name          isrc  \n",
       "0          469      1449      3032      52.0  1334  GBUM71602854  \n",
       "1          469      1449      3032      52.0  1334  GBUM71602854  \n",
       "2          469      1449      3032      52.0  1334  GBUM71602854  \n",
       "3          469      1449      3032      52.0  1334  GBUM71602854  \n",
       "4          469      1449      3032      52.0  1334  GBUM71602854  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 特征之间的相关系数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['msno', 'song_id', 'source_system_tab', 'source_screen_name',\n",
      "       'source_type', 'target', 'city', 'bd', 'gender', 'registered_via',\n",
      "       'registration_init_time', 'expiration_date', 'song_length', 'genre_ids',\n",
      "       'artist_name', 'composer', 'lyricist', 'language', 'name', 'isrc'],\n",
      "      dtype='object')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#获取所有列的名称\n",
    "cols = data.columns \n",
    "print(cols)\n",
    "# 计算所有组合的皮尔逊系数 ，通常认为相关系数大于0.5的为强相关\n",
    "feat_corr = data.corr().abs()\n",
    "\n",
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(feat_corr,annot=True)\n",
    "\n",
    "# 掩盖不重要的特征\n",
    "sns.heatmap(feat_corr, mask=feat_corr < 1, cbar=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#不能用于预测特征，drop\n",
    "#data.drop(['msno', 'song_id'],axis=1,inplace=True)\n",
    "#data.drop(['source_system_tab','target','expiration_date','song_length','genre_ids','composer', 'lyricist','name','isrc'],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "特征相关性不是很强，在后面考虑加正则项来处理加强相关性"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "保存训练数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.to_csv(dpath +'FE_train.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
